Search for dissertations about: "Machining system"
Showing result 21 - 25 of 68 swedish dissertations containing the words Machining system.
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21. On Monitoring and Control of Machining Processes
Abstract : The thesis presents several aspects related to the industrial and academic activities associated with monitoring and control of the machining process and machine tools A survey of the industrial situation identified some key factors for a successful implementation of monitoring and control techniques. Applicable, relatively simple, systems for cutting-process monitoring and adaptive control are available on the commercial market today but the degree of industrial utilisation of the technique is low because the systems are experienced as hard to operate and use, and are at the same time considered unreliable. READ MORE
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22. Advanced process monitoring and analysis of machining
Abstract : Milling is a processing technology massively applied in the metal manufacturing industry. The continuous demand for higher productivity and product quality asks for better understanding and control of the machining process. READ MORE
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23. Component Synthesis of Machine Tool and Cutter for Process Optimisation
Abstract : Metal cutting is today one of the leading forming processes in the manufacturing industry. The metal cutting industry houses several actors providing machine tools and cutting tools with a fierce competition as a consequence. Extensive efforts are made to improve the performance of both machine tools and cutting tools. READ MORE
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24. Machine Tool Dynamics - A constrained state-space substructuring approach
Abstract : Metal cutting is today one of the leading forming processes in the manufacturing industry. The metal cutting industry houses several actors providing machine tools and cutting tools with a fierce competition as a consequence. Extensive efforts are made to improve the performance of both machine tools and cutting tools. READ MORE
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25. Machine Learning and System Identification for Estimation in Physical Systems
Abstract : In this thesis, we draw inspiration from both classical system identification and modern machine learning in order to solve estimation problems for real-world, physical systems. The main approach to estimation and learning adopted is optimization based. READ MORE